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BrainViewRxTM provides visualization of functional and physiologic brain imaging data. The software package provides both analysis and viewing capabilities that promote the integration of physiologic and functional imaging data sets, including blood oxygen level dependent (BOLD) fMRI, magnetic resonance spectroscopy (MRS), and MR diffusion including diffusion tensor imaging (DT). The integration of these data, when interpreted by a trained physician, yields information that may assist in the diagnosis of brain pathology and the planning and monitoring of medical treatments.

BrainViewRx is an image processing software package for the visualization and manipulation of clinical imagery of multiple kinds. It brings sets of anatomical, physiologic and/or functional imagery into alignment and provides a variety of display and analysis options for utilizing the imagery relationships.

The Kyron™ Clinical Imaging BrainViewRx™ Viewer is an image processing software package for the visualization and manipulation of clinical imagery.

Here's an analysis of the acceptance criteria and study information provided in the 510(k) summary:

• Acceptance Criteria and Device Performance: The document states that "FDA has not established special controls or performance standards for this device." This means there were no specific quantitative acceptance criteria set by the FDA for this device to meet to demonstrate performance for a 510(k) submission. Instead, the performance evaluation focused on verification and validation of the software's proper function and its substantial equivalence to predicate devices.

  Therefore, a table of acceptance criteria and reported device performance as typically understood with quantitative metrics (e.g., sensitivity, specificity, accuracy) cannot be provided in this case, as such criteria were not explicitly defined or measured for this type of device in the context of this 510(k) submission. The "device performance" in this context refers to its ability to correctly implement its intended functions as a visualization and processing tool.

• Study That Proves the Device Meets Acceptance Criteria:
  The document indicates: "Software verification and validation was conducted to confirm proper function of the device's features." This statement describes the study performed.

  Here's a breakdown of the requested information:

  1. Table of Acceptance Criteria and Reported Device Performance:

     Acceptance Criteria (Implicit)	Reported Device Performance
     Proper function of device features (visualization, manipulation, alignment, display options)	Software verification and validation confirmed proper function.
     Substantial equivalence to predicate aesthetic imaging devices	BrainViewRx Viewer image display capabilities are substantially equivalent to Mirada Solutions Fusion 7D and MRI Devices Eloquence workstation. The selection of imagery displayed is substantially equivalent to Siemens syngo software.

  2. Sample size used for the test set and the data provenance: Not specified. The document only mentions "software verification and validation," which typically involves testing with various types of input data but does not provide details on the size or origin of such test data.

  3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not specified. For this type of software (visualization and processing), the "ground truth" would likely be the expected accurate rendering and manipulation of image data, as judged by software engineers, quality assurance personnel, and potentially medical professionals for usability and correctness of display. However, specific numbers or qualifications are not provided.

  4. Adjudication method for the test set: Not specified.

  5. If a multi-reader multi-case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance: No. This device is a viewer and processing tool, not an AI-powered diagnostic algorithm that assists human readers directly in interpretation to improve their performance in a way measurable by such a study. Its function is to present data.

  6. If a standalone (i.e., algorithm only without human-in-the-loop performance) was done: The "software verification and validation" study inherently evaluates the standalone performance of the algorithm in terms of its ability to process and display images as intended. However, no specific metrics for "standalone performance" in a diagnostic sense (e.g., sensitivity/specificity of an automatic detection or diagnosis) are provided as the device's function is not automated diagnosis.

  7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.): Not explicitly stated, but for software functionality, ground truth would be based on expected computational and display accuracy, possibly verified against known datasets or established imaging standards/benchmarks. Clinical correctness of displayed data would be implicitly verified by ensuring accurate representation of input medical images.

  8. The sample size for the training set: Not applicable. As an image processing software for visualization and manipulation, this device is unlikely to utilize a "training set" in the machine learning sense. Its functionality is based on algorithms that process data deterministically rather than learning from a dataset.

  9. How the ground truth for the training set was established: Not applicable, as there is no mention of a training set.

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